Taryn E Hassinger1, Christopher A Guidry1, Ori D Rotstein2, Therese M Duane3, Heather L Evans4, Charles H Cook5, Patrick J O'Neill6, John E Mazuski7, Reza Askari8, Lena M Napolitano9, Nicholas Namias10, Preston R Miller11, E Patchen Dellinger4, Raul Coimbra12, Christine S Cocanour13, Kaysie L Banton14, Joseph Cuschieri4, Kimberley Popovsky1, Robert G Sawyer1. 1. 1 Department of Surgery, The University of Virginia Health System , Charlottesville, Virginia. 2. 2 Department of Surgery, University of Toronto , Toronto, Ontario, Canada . 3. 3 Department of Surgery, University of North Texas John Peter Smith Hospital , Fort Worth, Texas. 4. 4 Department of Surgery, University of Washington , Seattle, Washington. 5. 5 Department of Surgery, Beth Israel Deaconess Medical Center , Boston, Massachusetts. 6. 6 Department of Surgery, Abrazo West Campus , Goodyear, Arizona. 7. 7 Department of Surgery, Washington University , St. Louis, Missouri. 8. 8 Department of Surgery, Brigham and Women's Hospital , Boston, Massachusetts. 9. 9 Department of Surgery, University of Michigan , Ann Arbor, Michigan. 10. 10 Department of Surgery, University of Miami Miller School of Medicine , Miami, Florida. 11. 11 Department of Surgery, Wake Forest School of Medicine , Winston-Salem, North Carolina. 12. 12 Department of Surgery, University of California , San Diego, San Diego, California. 13. 13 Department of Surgery, University of California Davis Medical Center , Sacramento, California. 14. 14 Department of Surgery, University of Minnesota Medical School , Minneapolis, Minnesota.
Abstract
BACKGROUND: Recent studies have suggested the length of treatment of intra-abdominal infections (IAIs) can be shortened without detrimental effects on patient outcomes. However, data from high-risk patient populations are lacking. We hypothesized that patients at high risk for treatment failure will benefit from a longer course of antimicrobial therapy. METHODS: Patients enrolled in the Study to Optimize Peritoneal Infection Therapy (STOP-IT) trial were evaluated retrospectively to identify risk factors associated with treatment failure, which was defined as the composite outcome of recurrent IAI, surgical site infection, or death. Variables were considered risk factors if there was a positive statistical association with treatment failure. Patients were then stratified according to the presence and number of these risk factors. Univariable analyses were performed using the Kruskal-Wallis, χ2, and Fisher exact tests. Logistic regression controlling for risk factors and original randomization group, either a fixed four-day antimicrobial regimen (experimental) or a longer course based on clinical response (control), also was performed. RESULTS: We identified corticosteroid use, Acute Physiology and Chronic Health Evaluation II score ≥5, hospital-acquired infection, or a colonic source of IAI as risk factors associated with treatment failure. Of the 517 patients enrolled, 263 (50.9%) had one or two risk factors and 16 (3.1%) had three or four risk factors. The rate of treatment failure rose as the number of risk factors increased. When controlling for randomization group, the presence and number of risk factors were independently associated with treatment failure, but the duration of antimicrobial therapy was not. CONCLUSIONS: We were able to identify patients at high risk for treatment failure in the STOP-IT trial. Such patients did not benefit from a longer course of antibiotic administration. Further study is needed to determine the optimum duration of antimicrobial therapy in high-risk patients.
BACKGROUND: Recent studies have suggested the length of treatment of intra-abdominal infections (IAIs) can be shortened without detrimental effects on patient outcomes. However, data from high-risk patient populations are lacking. We hypothesized that patients at high risk for treatment failure will benefit from a longer course of antimicrobial therapy. METHODS:Patients enrolled in the Study to Optimize Peritoneal Infection Therapy (STOP-IT) trial were evaluated retrospectively to identify risk factors associated with treatment failure, which was defined as the composite outcome of recurrent IAI, surgical site infection, or death. Variables were considered risk factors if there was a positive statistical association with treatment failure. Patients were then stratified according to the presence and number of these risk factors. Univariable analyses were performed using the Kruskal-Wallis, χ2, and Fisher exact tests. Logistic regression controlling for risk factors and original randomization group, either a fixed four-day antimicrobial regimen (experimental) or a longer course based on clinical response (control), also was performed. RESULTS: We identified corticosteroid use, Acute Physiology and Chronic Health Evaluation II score ≥5, hospital-acquired infection, or a colonic source of IAI as risk factors associated with treatment failure. Of the 517 patients enrolled, 263 (50.9%) had one or two risk factors and 16 (3.1%) had three or four risk factors. The rate of treatment failure rose as the number of risk factors increased. When controlling for randomization group, the presence and number of risk factors were independently associated with treatment failure, but the duration of antimicrobial therapy was not. CONCLUSIONS: We were able to identify patients at high risk for treatment failure in the STOP-IT trial. Such patients did not benefit from a longer course of antibiotic administration. Further study is needed to determine the optimum duration of antimicrobial therapy in high-risk patients.
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